| Chapter title |
Transcriptomic Analysis of Staphylococcus aureus Using Microarray and Advanced Next-Generation RNA-seq Technologies.
|
|---|---|
| Chapter number | 13 |
| Book title |
Methicillin-Resistant Staphylococcus Aureus (MRSA) Protocols
|
| Published in |
Methods in molecular biology, January 2014
|
| DOI | 10.1007/978-1-62703-664-1_13 |
| Pubmed ID | |
| Book ISBNs |
978-1-62703-663-4, 978-1-62703-664-1
|
| Authors |
Ting Lei, Aaron Becker, Yinduo Ji, Lei, Ting, Becker, Aaron, Ji, Yinduo |
| Abstract |
The transcriptome has shown tremendous potential for the comprehensive investigation of gene expression profiles and transcriptional levels in comparative biology, the identification of regulatory mechanism of transcriptional regulators, and the evaluation of target gene for developing new chemotherapeutic agents, vaccine, and diagnostic methods. The traditional microarray and advanced next-generation RNA sequencing technologies (RNA-seq) provide powerful and effective tools for the determination of the transcriptome of bacterial cells. In this chapter, we provide a detailed protocol for scientists who want to investigate gene expression profiles by performing microarray and/or RNA-seq analysis, including different RNA purification methods, mRNA enrichment, decontamination, cDNA synthesis, fragmentation, biotin labeling for hybridization using Affymetrix Staphylococcus aureus chips, quantitative real-time reverse transcription PCR, and RNA-seq data analysis. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 5% |
| Unknown | 20 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 38% |
| Student > Ph. D. Student | 6 | 29% |
| Other | 2 | 10% |
| Student > Master | 2 | 10% |
| Lecturer | 1 | 5% |
| Other | 2 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 48% |
| Medicine and Dentistry | 3 | 14% |
| Biochemistry, Genetics and Molecular Biology | 3 | 14% |
| Computer Science | 2 | 10% |
| Immunology and Microbiology | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 1 | 5% |